/*!
 * \file
 * \brief Eigenvalue decomposition functions.
 * \author Tony Ottosson
 *
 * -------------------------------------------------------------------------
 *
 * IT++ - C++ library of mathematical, signal processing, speech processing,
 *        and communications classes and functions
 *
 * Copyright (C) 1995-2009  (see AUTHORS file for a list of contributors)
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
 *
 * -------------------------------------------------------------------------
 */

#ifndef _MSC_VER
#  include <itpp/config.h>
#else
#  include <itpp/config_msvc.h>
#endif

#if defined(HAVE_LAPACK)
#  include <itpp/base/algebra/lapack.h>
#endif

#include <itpp/base/algebra/eigen.h>
#include <itpp/base/converters.h>


namespace itpp
{

#if defined(HAVE_LAPACK)

bool eig_sym(const mat &A, vec &d, mat &V)
{
  it_assert_debug(A.rows() == A.cols(), "eig_sym: Matrix is not symmetric");

  // Test for symmetric?

  char jobz = 'V', uplo = 'U';
  int n, lda, lwork, info;
  n = lda = A.rows();
  lwork = std::max(1, 3 * n - 1); // This may be choosen better!

  d.set_size(n, false);
  vec work(lwork);

  V = A; // The routine overwrites input matrix with eigenvectors

  dsyev_(&jobz, &uplo, &n, V._data(), &lda, d._data(), work._data(), &lwork, &info);

  return (info == 0);
}

bool eig_sym(const mat &A, vec &d)
{
  it_assert_debug(A.rows() == A.cols(), "eig_sym: Matrix is not symmetric");

  // Test for symmetric?

  char jobz = 'N', uplo = 'U';
  int n, lda, lwork, info;
  n = lda = A.rows();
  lwork = std::max(1, 3 * n - 1); // This may be choosen better!

  d.set_size(n, false);
  vec work(lwork);

  mat B(A); // The routine overwrites input matrix

  dsyev_(&jobz, &uplo, &n, B._data(), &lda, d._data(), work._data(), &lwork, &info);

  return (info == 0);
}

bool eig_sym(const cmat &A, vec &d, cmat &V)
{
  it_assert_debug(A.rows() == A.cols(), "eig_sym: Matrix is not hermitian");

  // Test for symmetric?

  char jobz = 'V', uplo = 'U';
  int n, lda, lwork, info;
  n = lda = A.rows();
  lwork = std::max(1, 2 * n - 1); // This may be choosen better!

  d.set_size(n, false);
  cvec work(lwork);
  vec rwork(std::max(1, 3*n - 2)); // This may be choosen better!

  V = A; // The routine overwrites input matrix with eigenvectors

  zheev_(&jobz, &uplo, &n, V._data(), &lda, d._data(), work._data(), &lwork, rwork._data(), &info);

  return (info == 0);
}

bool eig_sym(const cmat &A, vec &d)
{
  it_assert_debug(A.rows() == A.cols(), "eig_sym: Matrix is not hermitian");

  // Test for symmetric?

  char jobz = 'N', uplo = 'U';
  int n, lda, lwork, info;
  n = lda = A.rows();
  lwork = std::max(1, 2 * n - 1); // This may be choosen better!

  d.set_size(n, false);
  cvec work(lwork);
  vec rwork(std::max(1, 3*n - 2)); // This may be choosen better!

  cmat B(A); // The routine overwrites input matrix

  zheev_(&jobz, &uplo, &n, B._data(), &lda, d._data(), work._data(), &lwork, rwork._data(), &info);

  return (info == 0);
}


// Non-symmetric matrix
bool eig(const mat &A, cvec &d, cmat &V)
{
  it_assert_debug(A.rows() == A.cols(), "eig: Matrix is not square");

  char jobvl = 'N', jobvr = 'V';
  int n, lda, ldvl, ldvr, lwork, info;
  n = lda = A.rows();
  ldvl = 1;
  ldvr = n;
  lwork = std::max(1, 4 * n); // This may be choosen better!

  vec work(lwork);
  vec rwork(std::max(1, 2*n)); // This may be choosen better
  vec wr(n), wi(n);
  mat vl, vr(n, n);

  mat B(A); // The routine overwrites input matrix

  dgeev_(&jobvl, &jobvr, &n, B._data(), &lda, wr._data(), wi._data(), vl._data(), &ldvl, vr._data(), &ldvr, work._data(), &lwork, &info);

  d = to_cvec(wr, wi);

  // Fix V
  V.set_size(n, n, false);
  for (int j = 0; j < n; j++) {
    // if d(j) and d(j+1) are complex conjugate pairs, treat special
    if ((j < n - 1) && d(j) == std::conj(d(j + 1))) {
      V.set_col(j, to_cvec(vr.get_col(j), vr.get_col(j + 1)));
      V.set_col(j + 1, to_cvec(vr.get_col(j), -vr.get_col(j + 1)));
      j++;
    }
    else {
      V.set_col(j, to_cvec(vr.get_col(j)));
    }
  }

  return (info == 0);
}

// Non-symmetric matrix
bool eig(const mat &A, cvec &d)
{
  it_assert_debug(A.rows() == A.cols(), "eig: Matrix is not square");

  char jobvl = 'N', jobvr = 'N';
  int n, lda, ldvl, ldvr, lwork, info;
  n = lda = A.rows();
  ldvl = 1;
  ldvr = 1;
  lwork = std::max(1, 4 * n); // This may be choosen better!

  vec work(lwork);
  vec rwork(std::max(1, 2*n)); // This may be choosen better
  vec wr(n), wi(n);
  mat vl, vr;

  mat B(A); // The routine overwrites input matrix

  dgeev_(&jobvl, &jobvr, &n, B._data(), &lda, wr._data(), wi._data(), vl._data(), &ldvl, vr._data(), &ldvr, work._data(), &lwork, &info);

  d = to_cvec(wr, wi);

  return (info == 0);
}

bool eig(const cmat &A, cvec &d, cmat &V)
{
  it_assert_debug(A.rows() == A.cols(), "eig: Matrix is not square");

  char jobvl = 'N', jobvr = 'V';
  int n, lda, ldvl, ldvr, lwork, info;
  n = lda = A.rows();
  ldvl = 1;
  ldvr = n;
  lwork = std::max(1, 2 * n); // This may be choosen better!

  d.set_size(n, false);
  V.set_size(n, n, false);
  cvec work(lwork);
  vec rwork(std::max(1, 2*n)); // This may be choosen better!
  cmat vl;

  cmat B(A); // The routine overwrites input matrix

  zgeev_(&jobvl, &jobvr, &n, B._data(), &lda, d._data(), vl._data(), &ldvl, V._data(), &ldvr, work._data(), &lwork, rwork._data(), &info);


  return (info == 0);
}

bool eig(const cmat &A, cvec &d)
{
  it_assert_debug(A.rows() == A.cols(), "eig: Matrix is not square");

  char jobvl = 'N', jobvr = 'N';
  int n, lda, ldvl, ldvr, lwork, info;
  n = lda = A.rows();
  ldvl = 1;
  ldvr = 1;
  lwork = std::max(1, 2 * n); // This may be choosen better!

  d.set_size(n, false);
  cvec work(lwork);
  vec rwork(std::max(1, 2*n)); // This may be choosen better!
  cmat vl, vr;

  cmat B(A); // The routine overwrites input matrix

  zgeev_(&jobvl, &jobvr, &n, B._data(), &lda, d._data(), vl._data(), &ldvl, vr._data(), &ldvr, work._data(), &lwork, rwork._data(), &info);


  return (info == 0);
}

#else

bool eig_sym(const mat &A, vec &d, mat &V)
{
  it_error("LAPACK library is needed to use eig_sym() function");
  return false;
}

bool eig_sym(const mat &A, vec &d)
{
  it_error("LAPACK library is needed to use eig_sym() function");
  return false;
}

bool eig_sym(const cmat &A, vec &d, cmat &V)
{
  it_error("LAPACK library is needed to use eig_sym() function");
  return false;
}

bool eig_sym(const cmat &A, vec &d)
{
  it_error("LAPACK library is needed to use eig_sym() function");
  return false;
}


bool eig(const mat &A, cvec &d, cmat &V)
{
  it_error("LAPACK library is needed to use eig() function");
  return false;
}

bool eig(const mat &A, cvec &d)
{
  it_error("LAPACK library is needed to use eig() function");
  return false;
}

bool eig(const cmat &A, cvec &d, cmat &V)
{
  it_error("LAPACK library is needed to use eig() function");
  return false;
}

bool eig(const cmat &A, cvec &d)
{
  it_error("LAPACK library is needed to use eig() function");
  return false;
}

#endif // HAVE_LAPACK

vec eig_sym(const mat &A)
{
  vec d;
  eig_sym(A, d);
  return d;
}

vec eig_sym(const cmat &A)
{
  vec d;
  eig_sym(A, d);
  return d;
}


cvec eig(const mat &A)
{
  cvec d;
  eig(A, d);
  return d;
}

cvec eig(const cmat &A)
{
  cvec d;
  eig(A, d);
  return d;
}

} //namespace itpp
